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Model A
Claude Opus 4.7

Anthropic

70.29/100

Supported · Public rank #17

90% interval 63.976.7

Claude Opus 4.7 vs Claude Sonnet 5

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Anthropic logo
Model B
Claude Sonnet 5

Anthropic

69.84/100

Supported · Public rank #20

90% interval 66.773.0

Decision reading

Claude Opus 4.7 has the higher public score estimate, 70.29 versus 69.84, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

6 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Coding work

    Code generation, repair, and software-engineering tasks

    Claude Sonnet 5

    Claude Sonnet 5 leads on the public coding lane, 64 to 62.7, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Claude Sonnet 5

    Claude Sonnet 5 leads on the public agentic lane, 65.8 to 55.8, with Supported evidence for both models, although the 90% intervals overlap.

    Confidence: limited

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude Sonnet 5

    Claude Sonnet 5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls
  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Claude Sonnet 5

    Claude Sonnet 5 has the lower estimated token cost for this stated workload. Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Claude Sonnet 5

    Claude Sonnet 5 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
6
Claude Opus 4.7 only
7
Claude Sonnet 5 only
18
Like-for-like categories
2 / 8

1 category rests on Estimated evidence or different evidence sets. Those rows remain visible for coverage context but do not name a winner.

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Like-for-like
Claude Opus 4.7
55.8
Supported · #36/152
Claude Sonnet 5
65.8
Supported · #11/152
Basis
BenchAlign lane · 4 vs 6 public rows
Reading
Claude Sonnet 5 leads · intervals overlap

Coding

Like-for-like
Claude Opus 4.7
62.7
Supported · #14/151
Claude Sonnet 5
64.0
Supported · #13/151
Basis
BenchAlign lane · 5 vs 10 public rows
Reading
Claude Sonnet 5 leads · intervals overlap

Knowledge

Directional only
Claude Opus 4.7
64.6
Estimated · #26/183
Claude Sonnet 5
66.6
Supported · #20/183
Basis
BenchAlign lane · 2 vs 6 public rows
Reading
Directional only

Reasoning

Not comparable
Claude Opus 4.7
Not ranked
Claude Sonnet 5
77.4
Unranked · 2 rankable rows
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Math

Not comparable
Claude Opus 4.7
60.8
Unranked · 2 rankable rows
Claude Sonnet 5
Not ranked
Basis
Provisional lane · 2 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Opus 4.7
Not ranked
Claude Sonnet 5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Opus 4.7
Not ranked
Claude Sonnet 5
77.5
#13/48
Basis
Provisional lane · 0 vs 1 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Opus 4.7
Not ranked
Claude Sonnet 5
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

Too few matched category axes support a radar. The ruled list below shows only shared benchmark results; positions use each benchmark’s normalized display scale when available.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Opus 4.7
$0.0175
Fits in one request
Claude Sonnet 5
$0.007
Fits in one request

Claude Sonnet 5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Opus 4.7
$0.325
Fits in one request
Claude Sonnet 5
$0.13
Fits in one request

Claude Sonnet 5 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Opus 4.7
$1.35
Fits in one request
Cached input priced at the published list-input rate
Claude Sonnet 5
$0.18
Fits in one request

Claude Sonnet 5 has the lower modeled cost

Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Opus 4.7

Not published

Claude Sonnet 5

$0.2 per 1M cached input tokens

Claude API pricing

Reasoning profile

Claude Opus 4.7

Non-Reasoning

Claude Sonnet 5

Reasoning

Weight access

Claude Opus 4.7

Proprietary

Claude Sonnet 5

Proprietary

License

Claude Opus 4.7

Proprietary

Claude Sonnet 5

Proprietary

Release date

Claude Opus 4.7

2026-04-16

Claude Sonnet 5

2026-06-30

If you already use one of these models
Deployment change
Both entries list Anthropic as the provider. Confirm endpoint, model ID, limits, and feature support before switching.
Quality signal
Claude Opus 4.7 has the higher public score estimate, 70.29 versus 69.84, but the 90% score intervals overlap.
Workload cost
Repository review: $0.325 vs $0.13. Cache-heavy agent loop: $1.35 vs $0.18.
Context tradeoff
Both models list 1M.

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence31 rows

Agentic

  • Gert Labs

    Claude Opus 4.765.59%
    Source
    Claude Sonnet 5

    Not directly comparable

  • ResearchClawBench

    Claude Opus 4.720.7%
    Source
    Claude Sonnet 5

    Not directly comparable

  • OSWorld 2.0

    Claude Opus 4.713.9%
    Source
    Claude Sonnet 5

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Opus 4.768.5%
    Source
    Claude Sonnet 574.5%
    Source

    Claude Sonnet 5 leads this result

  • Terminal-Bench 3.0

    Claude Opus 4.7
    Claude Sonnet 514.6%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.7
    Claude Sonnet 580.4%
    Source

    Not directly comparable

  • BrowseComp

    Claude Opus 4.7
    Claude Sonnet 584.7%
    Source

    Not directly comparable

  • HLE w/ tools

    Claude Opus 4.7
    Claude Sonnet 557.4%
    Source

    Not directly comparable

  • OSWorld-Verified

    Claude Opus 4.7
    Claude Sonnet 581.2%
    Source

    Not directly comparable

Coding

  • Vibe Code Bench

    Claude Opus 4.771.00%
    Source
    Claude Sonnet 5

    Not directly comparable

  • React Native Evals

    Claude Opus 4.782.8%
    Source
    Claude Sonnet 5

    Not directly comparable

  • FrontierCode 1.1 Main

    Shared source
    Claude Opus 4.738.5%
    Claude Sonnet 542.7%

    Claude Sonnet 5 leads this result

  • LiveCodeBench (Vals)

    Claude Opus 4.785.1%
    Source
    Claude Sonnet 582.4%
    Source

    Claude Opus 4.7 leads this result

  • SWE-bench (Vals)

    Claude Opus 4.782.0%
    Source
    Claude Sonnet 579.6%
    Source

    Claude Opus 4.7 leads this result

  • SWE-bench Verified

    Claude Opus 4.7
    Claude Sonnet 585.2%
    Source

    Not directly comparable

  • SWE-bench Pro

    Claude Opus 4.7
    Claude Sonnet 563.2%
    Source

    Not directly comparable

  • SWE Multilingual

    Claude Opus 4.7
    Claude Sonnet 578.3%
    Source

    Not directly comparable

  • SWE Multimodal

    Claude Opus 4.7
    Claude Sonnet 528.1%
    Source

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Opus 4.7
    Claude Sonnet 580.4%
    Source

    Not directly comparable

  • cursorBench32

    Claude Opus 4.7
    Claude Sonnet 561.5%
    Source

    Not directly comparable

  • VulcanBench CII v1

    Claude Opus 4.7
    Claude Sonnet 589.2%
    Source

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Opus 4.790.2%
    Source
    Claude Sonnet 588.9%
    Source

    Claude Opus 4.7 leads this result

  • MMLU-Pro (Vals)

    Claude Opus 4.789.9%
    Source
    Claude Sonnet 587.5%
    Source

    Claude Opus 4.7 leads this result

  • HLE

    Claude Opus 4.7
    Claude Sonnet 557.4%
    Source

    Not directly comparable

  • HLE w/o tools

    Claude Opus 4.7
    Claude Sonnet 543.2%
    Source

    Not directly comparable

  • HLE-Verified

    Claude Opus 4.7
    Claude Sonnet 531.0%
    Source

    Not directly comparable

  • LABBench2

    Claude Opus 4.7
    Claude Sonnet 580.1%
    Source

    Not directly comparable

Math

  • FrontierMath v2 (Tiers 1-3)

    Claude Opus 4.743.793%
    Source
    Claude Sonnet 5

    Not directly comparable

  • FrontierMath v2 (Tier 4)

    Claude Opus 4.722.917%
    Source
    Claude Sonnet 5

    Not directly comparable

Multimodal

  • CharXiv

    Claude Opus 4.7
    Claude Sonnet 588.3%
    Source

    Not directly comparable

  • CharXiv w/o tools

    Claude Opus 4.7
    Claude Sonnet 577%
    Source

    Not directly comparable

Frequently asked questions

Which is better, Claude Opus 4.7 or Claude Sonnet 5?

Claude Opus 4.7 has the higher public score estimate, 70.29 versus 69.84, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Opus 4.7 or Claude Sonnet 5?

Claude Sonnet 5 leads the public coding lane, 64 to 62.7, with Supported evidence for both models, although the 90% intervals overlap.

Which is better for agentic tasks, Claude Opus 4.7 or Claude Sonnet 5?

Claude Sonnet 5 leads the public agentic tasks lane, 65.8 to 55.8, with Supported evidence for both models, although the 90% intervals overlap.

Which costs less, Claude Opus 4.7 or Claude Sonnet 5?

For the stated presets, chat costs $0.0175 on Claude Opus 4.7 and $0.007 on Claude Sonnet 5; repository review costs $0.325 and $0.13; the cache-heavy agent loop costs $1.35 and $0.18. Claude Opus 4.7 has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Opus 4.7 or Claude Sonnet 5?

Both models list the same context window, 1M.

Related comparisons

Last updated September 10, 2026

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